• Title/Summary/Keyword: Nonparametric Additive Risk Model

Search Result 4, Processing Time 0.027 seconds

A Nonparametric Additive Risk Model Based on Splines

  • Park, Cheol-Yong
    • Journal of the Korean Data and Information Science Society
    • /
    • v.18 no.1
    • /
    • pp.97-105
    • /
    • 2007
  • We consider a nonparametric additive risk model that is based on splines. This model consists of both purely and smoothly nonparametric components. As an estimation method of this model, we use the weighted least square estimation by Huller and Mckeague (1991). We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least square method.

  • PDF

A Nonparametric Additive Risk Model Based On Splines

  • Park, Cheol-Yong
    • 한국데이터정보과학회:학술대회논문집
    • /
    • 2006.11a
    • /
    • pp.49-50
    • /
    • 2006
  • We consider a nonparametric additive risk model that are based on splines. This model consists of both purely and smoothly nonparametric components. As an estimation method of this model, we use the weighted least square estimation by Huffer and McKeague (1991). We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least square method.

  • PDF

A General Semiparametric Additive Risk Model

  • Park, Cheol-Yong
    • Journal of the Korean Data and Information Science Society
    • /
    • v.19 no.2
    • /
    • pp.421-429
    • /
    • 2008
  • We consider a general semiparametric additive risk model that consists of three components. They are parametric, purely and smoothly nonparametric components. In parametric component, time dependent term is known up to proportional constant. In purely nonparametric component, time dependent term is an unknown function, and time dependent term in smoothly nonparametric component is an unknown but smoothly function. As an estimation method of this model, we use the weighted least square estimation by Huffer and McKeague (1991). We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least square method.

  • PDF

A Time-Series Study of Ambient Air Pollution in Relation to Daily Mortality in Seoul, 1998∼2001 (서울시 대기오염과 일별 사망의 상관성에 관한 시계열적 연구 (1998∼2001년))

  • Cho, Yong-Sung;Lee, Jong-Tae;Kim, Yoon-Sin;Hong, Seung-Cheol;Kim, Ho;Ha, Eun-Hee;Park, Hye-Sook;Lee, Bo-Eun
    • Journal of Korean Society for Atmospheric Environment
    • /
    • v.19 no.6
    • /
    • pp.625-637
    • /
    • 2003
  • This study was performed to examine the relationship between air pollution exposure and mortality in Seoul for the years of 1998∼2001. Daily counts of death were analyzed by general additive Poisson model, with adjustment for effects of seasonal trend, air temperature, humidity, and day of the week as confounders in a nonparametric approach. Daily death counts were associated with CO (current day),O$_3$ (current day), PM$_{10}$ (current day), NO$_2$ (1 day before), SO$_2$ (1 day before). Increase of 41.71 $\mu\textrm{g}$/㎥ (interquartile range) in PM$_{10}$ was associated with 1.3% (95% CI = 0.7∼1.9%) increase in the daily number of death. $O_3$ concentrations resulted in an increased risk of 1.3% for 23.86 ppb in all-aged mortality [RR = 1.013 (1.004-1.023)1. This effect was greater in children (less than 15 aged) and elderly (more than 65 aged). After ozone level exceeds 25 ppb, the dose-response relationship between mortality and ozone was almost linear. We concluded that Seoul had 1∼5% increase in mortality in association with IQR (interquartile range) in air pollutants. Daily variations in air pollution within the range currently occurring in Seoul might have an adverse effect on daily mortality. These findings also support the hypothesis that air pollution, at levels below the current ambient air quality standards of Korea, is harmful to sensitive subjects, such as children or elderly.rly.